Privacy Aware Stochastic Games for Distributed End-User Energy Storage Sharing

• Published in: IEEE transactions on signal and information processing over networks 2018-03, Vol.4 (1), p.82-95
• Main Authors: Yao, Jiyun, Venkitasubramaniam, Parv
• Format: Article
• Language: English
• Subjects: Batteries; Demand response; energy management; Games; Load management; non-stationary strategy; Pricing; Privacy; Renewable energy sources; smart grids; stochastic game; storage sharing
• ISSN: 2373-776X; 2373-776X; 2373-7778
• DOI: 10.1109/TSIPN.2017.2778945

Deregulated electricity markets with time-varying electricity prices and opportunities for consumer cost mitigation makes energy storage, such as a battery, an attractive proposition. Sharing a large capacity battery across a group of homes in a community can not only alleviate the economic deterrents but also exploit the fact that users' activity patterns do not necessarily overlap. However, battery sharing induces competition for battery capacity between the users in general as they may want to maximize their own cost savings by occupying more battery capacity when the electricity price is low. Importantly, users might have privacy concerns when they communicate with the shared battery controller. The privacy aware management of such a shared battery is the focus of this paper. A game theoretical framework is proposed to capture the competitive behaviors of users sending messages through a communication network to an independent battery controller with an infinite horizon limiting average signaling game formulation. The privacy requirement serves as a constraint on messaging behaviors. The battery controller manages the charging and discharging based on the received, albeit incomplete, information transmission. With such a framework, we study the battery sharing when users are cooperative and completely private. When the privacy requirement is relaxed, the competitive behaviors of users sending messages to the battery controller is studied. A credit-based battery management strategy is designed for the battery controller to ensure an equilibrium of the game and achieves the social optimality. However, the credit-based battery management requires long time established observations and may also "coerce" users to share their energy demands accurately with the controller. We, therefore, propose a class of stationary suboptimal privacy preserving battery management strategy in which the message set being restricted to be completely private or partially private. In addition, we demonstrate that by changing the size of the message set, different pairs of preserved privacy and cost savings can be achieved. Through numerical simulations on real electricity pricing and usage data, we demonstrate the cost effectiveness of battery capacity sharing and the tradeoff between privacy and cost mitigation.